75 research outputs found

    Extinction of Taurus, Orion, Perseus and California Molecular Clouds Based on the LAMOST, 2MASS and Gaia surveys I: Three-dimensional Extinction and Structure

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    The three-dimensional extinction and structure are studied for the Taurus, Orion, Perseus and California molecular clouds based on the LAMOST spectroscopy. Stellar color excess is calculated with the intrinsic color index derived from the atmospheric parameters in the LAMOST DR8 catalog and the observed color index in the Gaia EDR3 and the 2MASS PSC. In combination with the distance from the Gaia EDR3 parallax, the three-dimensional dust extinction maps are retrieved in the color excesses EGBP,GRPE_{\rm{G_{BP},G_{RP}}} and EJ,KSE_{\rm{J,K_{S}}} with an uncertainty of ∼\sim0.03mag and ∼\sim0.07mag respectively. The extinction maps successfully separate the clouds that overlap in the sky area and manifest the structure of the individual cloud. Meanwhile, a bow-like structure is found with a distance range from 175pc to 250pc, half of which is a part of the Per-Tau Shell in similar coordinates and distance while the other half is not. Three low-extinction rings are additionally discovered and briefly discussed.Comment: 22 pages, 15 figures, 2 tables, accepted for publication in Ap

    SPar: estimating stellar parameters from multi-band photometries with empirical stellar libraries

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    Modern large-scale photometric surveys have provided us with multi-band photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (\teff) and metallicities (\feh), absolute magnitudes (MGM_{G}), distances (dd) and reddening values (\ebr) is fundamental to study the stellar populations, structure, kinematics and chemistry of the Galaxy. This work constructed an empirical stellar library which maps the stellar parameters to multi-band photometries from a dataset with Gaia parallaxes, LAMOST atmospheric parameters, and optical to near-infrared photometry from several photometric surveys. Based on the stellar library, we developed a new algorithm, SPar (\textbf{S}tellar \textbf{P}arameters from multib\textbf{a}nd photomet\textbf{r}y), which fits the multi-band stellar photometries to derive the stellar parameters (\teff, \feh, MGM_G, dd and \ebr) of the individual stars. The algorithm is applied to the multi-band photometric measurements of a sample of stars selected from the SMSS survey, which have stellar parameters derived from the spectroscopic surveys. The stellar parameters derived from multi-band photometries by our algorithm are in good agreement with those from the spectroscopic surveys. The typical differences between our results and the literature values are 170\,K for \teff, 0.23\,dex for \feh, 0.13\,mag for MGM_G and 0.05\,mag for \ebr. The algorithm proved to be robust and effective and will be applied to the data of future large-scale photometric surveys such as the Mephisto and CSST surveys.Comment: 16 pages, 10 figures, Accepted by The Astronomical Journal on 7/8/202

    A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network

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    In a home energy management system (HEMS), appliances are becoming diversified and intelligent, so that certain simple maintenance work can be completed by appliances themselves. During the measurement, collection and transmission of electricity load data in a HEMS sensor network, however, problems can be caused on the data due to faulty sensing processes and/or lost links, etc. In order to ensure the quality of retrieved load data, different solutions have been presented, but suffered from low recognition rates and high complexity. In this paper, a validation and repair method is presented to detect potential failures and errors in a domestic energy management system, which can then recover determined load errors and losses. A Kernel Extreme Learning Machine (K-ELM) based model has been employed with a Radial Basis Function (RBF) and optimised parameters for verification and recognition; whilst a Dual-spline method is presented to repair missing load data. According to the experiment results, the method outperforms the traditional B-spline and Cubic-spline methods and can effectively deal with unexpected data losses and errors under variant loss rates in a practical home environment

    A Survey of Lower Limb Rehabilitation Systems and Algorithms Based on Functional Electrical Stimulation

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    Functional electrical stimulation is a method of repairing a dysfunctional limb in a stroke patient by using low-intensity electrical stimulation. Currently, it is widely used in smart medical treatment for limb rehabilitation in stroke patients. In this paper, the development of FES systems is sorted out and analyzed in a time order. Then, the progress of functional electrical stimulation in the field of rehabilitation is reviewed in details in two aspects, i.e., system development and algorithm progress. In the system aspect, the development of the first FES control and stimulation system, the core of the lower limb-based neuroprosthesis system and the system based on brain-computer interface are introduced. The algorithm optimization for control strategy is introduced in the algorithm. Asynchronous stimulation to prolong the function time of the lower limbs and a method to improve the robustness of knee joint modeling using neural networks. Representative applications in each of these aspects have been investigated and analyzed

    An Auto-Calibration Approach to Robust and Secure Usage of Accelerometers for Human Motion Analysis in FES Therapies

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    A Functional Electrical stimulation (FES) therapy is a common rehabilitation intervention after stroke, and finite state machine (FSM) has proven to be an effective and intuitive FES control method. The FSM uses the data information generated by the accelerometer to robustly trigger state transitions. In the medical field, it is necessary to obtain highly safe and accurate acceleration data. In order to ensure the accuracy of the acceleration sensor data without affecting the accuracy of the motion analysis, we need to perform acceleration big data calibration. In this context, we propose a method for robustly calculating the auto-calibration gain using redundant acceleration vectors, and then calibrating the data generated by the accelerometer based on the calculated gain. The selection of the acceleration vector involved in the gain calculation is demonstrated by different experiments. The results show that the auto-calibration gain calculated after calibration is very close to 1, and the error is significantly less than before calibration, which indicates that the accelerometer unit is well calibrated

    The measurement of masses of OB-type stars from LAMOST DR5

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    The measurements of masses and luminosities of massive stars play an important role in understanding the formation and evolution of their host galaxies. In this work, we present the measurement of masses and luminosities of 2,946 OB-type stars, including 78 O-type stars and 2,868 B-type stars, based on their stellar parameters (effective temperature, surface gravity, and metallicity) and PARSEC isochrones model. Our results show that the median mass and luminosity of the 2,946 OB-type stars are 5.4 M⊙_{\odot} and log(L/L⊙_{\odot})=3.2 with the median relative error of 21.4%\% and 71.1%\%, respectively. A good agreement between our results estimated by using our method and those derived by using the orbital motions of binary stars from the literature is found for some B-type stars. In addition, we also fit the mass-luminosity relation of B-type stars by using our derived mass and the luminosity from GaiaGaia DR3.Comment: 12 pages, 10 figures, 1 table, accepted for publication in ApJ

    Identification of Blue Horizontal-Branch Stars From LAMOST DR5

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    We construct a new catalog of the blue horizontal-branch (BHB) stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR5 dataset, which contains 5355+81 BHB stars at high Galactic latitude ((∣Glat∣>20∘|Glat|>20^{\circ}). We combine the spectral line indices with a set of Balmer line profile selection criteria to identify the BHB stars. During the selection process, we use the line index of \ion{Ca}{2}\,K to exclude the metal-rich A-type dwarfs. We obtain their atmospheric parameters by cross-matching our BHB stars with the catalog provided by \citet{Xiang2022}. The results show that our sample is consistent with the theoretical TeffT_{\rm eff}-log\,gg evolutionary tracks of the BHB stars, indicating that our method is robust for identifying BHB stars from the LAMOST spectra. Their spatial distribution indicates that most of our BHB stars are located in the inner halo or the disk of the Milky Way. Combined with other BHB samples from the literature, the BHB stars can cover a large Galactic volume, which makes it a better probe for studying the kinematics, dynamics, and structural characteristics of the Milky Way.Comment: accepted by ApJS.15 pages, 18 figure
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